Drilling Fluid Additive Modeling for Precise Property Control
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Solution Overview
Problem
Conventional methods for managing drilling fluid properties during downhole drilling operations are imprecise and costly, relying on trial and error and extensive experience, leading to unpredictable consequences and reduced drilling effectiveness due to unpredictable additive interactions.
Innovation Solution
A multi-dimensional drilling additive model is used to correlate the effects of various additives on drilling fluid properties, allowing for precise determination of additive amounts to maintain setpoint properties through an inverted model and optimization functions, reducing reliance on human expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional trial and error methods are used to determine additive amounts, then the process relies on extensive human experience, but the precision and predictability of maintaining drilling fluid properties deteriorates
Solution Approach 1:
The patent replaces the manual trial-and-error process with a computational system that uses mathematical models and algorithms to automatically determine optimal additive amounts. The system substitutes human expertise with computer-based calculations that precisely predict additive interactions and their effects on drilling fluid properties.
Solution Approach 2:
The patent creates a virtual model (digital twin) of the drilling fluid system that replicates the complex interactions between multiple additives and fluid properties. This computational copy allows for precise prediction and optimization without requiring extensive physical experimentation or human trial-and-error.
2Adaptability or versatility
If multiple additives are used to adjust drilling fluid properties, then the ability to change fluid properties is improved, but the predictability of additive interactions and consequences deteriorates
Solution Approach 1:
The patent performs preliminary computational analysis before actual additive application. The system calculates the effects of multiple additive combinations in advance using mathematical models, allowing operators to predict outcomes and select the most effective combination before implementing changes in the actual drilling fluid system.
Solution Approach 2:
The patent implements a feedback mechanism where the results of additive applications are measured and fed back into the computational model. This allows the system to continuously refine its predictions and improve the reliability of interaction predictions for future additive decisions, creating a learning system that becomes more accurate over time.
3Ease of operation
If extensive human expertise is used to manage drilling fluid additives, then the ability to handle complex fluid properties is improved, but the cost and time required for the process increases
Solution Approach 1:
The patent enables the drilling fluid management system to serve itself by automatically determining optimal additive amounts without requiring continuous human intervention. The computational system independently analyzes fluid properties, predicts additive effects, and recommends or automatically implements additive dosing decisions, freeing operators from time-consuming manual management tasks.
4Productivity
If trial and error methods are used for additive management, then the process is simpler to implement, but the drilling effectiveness and operational efficiency deteriorates
Solution Approach 1:
The patent systematically varies and optimizes multiple parameters simultaneously (additive types, concentrations, combinations) using computational methods. Rather than changing one parameter at a time through trial and error, the system evaluates multiple parameter combinations in parallel through mathematical modeling, rapidly identifying the optimal set of parameters for maximizing drilling effectiveness.
Data Source
AI summary
A drilling fluid manager creates a multi-dimensional drilling fluid additive model and interpolates changes in a drilling fluid based on a combination of additives. The interpolations are inverted to determine the amount of additives based on measurements of drilling fluid properties. As fluid is returned to the surface, drilling fluid parameters are measured. A difference between the measured fluid parameters and setpoint fluid properties and the inverted interpolations are used to determine the amounts of each additive.


